Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis.

Peritoneal carcinomatosis (PC) is a type of secondary cancer which is not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making the early diagnosis, individualized treatment, and accurate prognostic evaluation of various cancers, including mediastinal malignancies, colorectal cancer, lung cancer more feasible. As a branch of computer science, AI specializes in image recognition, speech recognition, automatic large-scale data extraction and output. AI technologies have also made breakthrough progress in the field of peritoneal carcinomatosis (PC) based on its powerful learning capacity and efficient computational power. AI has been successfully applied in various approaches in PC diagnosis, including imaging, blood tests, proteomics, and pathological diagnosis. Due to the automatic extraction function of the convolutional neural network and the learning model based on machine learning algorithms, AI-assisted diagnosis types are associated with a higher accuracy rate compared to conventional diagnosis methods. In addition, AI is also used in the treatment of peritoneal cancer, including surgical resection, intraperitoneal chemotherapy, systemic chemotherapy, which significantly improves the survival of patients with PC. In particular, the recurrence prediction and emotion evaluation of PC patients are also combined with AI technology, further improving the quality of life of patients. Here we have comprehensively reviewed and summarized the latest developments in the application of AI in PC, helping oncologists to comprehensively diagnose PC and provide more precise treatment strategies for patients with PC.

Combining Anti-epidermal Growth Factor Receptor (EGFR) Therapy with Immunotherapy in Metastatic Colorectal Cancer (mCRC).

INTRODUCTION: Monoclonal antibodies binding the EGFR, such as cetuximab and panitumumab, have been extensively used as targeted therapy for the treatment of mCRC. However, in clinical practice, it has been found that these treatment options have some limitations and fail to fully exploit their immunoregulatory activities. Meanwhile, because of the limited effects of current treatments, immunotherapy is being widely studied for patients with mCRC. However, previous immunotherapy trials in mCRC patients have had unsatisfactory outcomes as monotherapy. Thus, combinatorial treatment strategies are being researched. AREAS COVERED: The authors retrieved relevant documents of combination therapy for mCRC from PubMed and Medline. This review elaborates on the knowledge of immunomodulatory effects of anti-EGFR therapy alone and in combination with immunotherapy for mCRC. EXPERT OPINION: Although current treatment options have improved median overall survival (OS) for advanced disease to 30 months, the prognosis remains challenging for those with metastatic disease. More recently, the combination of anti-EGFR therapy with immunotherapy has been shown activity with complementary mechanisms. Hence, anti-EGFR therapy in combination with immunotherapy may hold the key to improving the therapeutic effect of refractory mCRC.

Peritoneal carcinomatosis with intraperitoneal immunotherapy: current treatment options and perspectives.

INTRODUCTION: Peritoneal carcinomatosis (PC) is an advanced malignancy that is not sensitive to systemic conventional chemotherapy. Treatment options for PC are usually palliative rather than curative. Cytoreductive surgery and hyperthermic intraperitoneal (IP) chemotherapy are associated with limited efficacy in patients with PC. However, the peritoneum can produce effective immunity by inducing T-lymphocyte recruitment and proliferation, and the unique immune environment of the peritoneum provides the rationale for IP immunotherapy in PC. AREAS COVERED: The authors retrieved relevant documents of IP immunotherapy for PC from PubMed and Medline. This review elaborates on the knowledge of the peritoneal immune microenvironment and IP immunotherapy for PC covering immune stimulators, radioimmunotherapy, catumaxomab, cancer vaccines, chimeric antigen receptor (CAR)-T cells, and immune checkpoint inhibitors. EXPERT OPINION: The prognosis of PC is poor. However, the peritoneal cavity is a unique immune compartment with abundant immune cells which can produce effective immunity. IP immunotherapy may be a promising strategy in patients with PC.

Clinical characteristics and prognostic factors of anal adenocarcinoma: a nomogram development based on SEER database and validation in the WCH database.

PURPOSE: The purpose of this study was to comprehensively understand anal canal adenocarcinomas (AA) and develop a nomogram for prognostic prediction of AA. METHODS: Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (the year 2004-2015). An external validation set was collected from West China Hospital (WCH) databases. Propensity-score matching (PSM) was performed to balance the demographic characteristic. A novel nomogram was developed to estimate individual survival probability and its performance was validated using the concordance index (C-index), calibration curves, and decision curve analyses (DCA). RESULTS: A total of 7901 patients were enrolled including 749 AA patients and 7152 squamous cell carcinomas of the anal canal (ASCC) patients. Before PSM, patients with AA had shorter cancer-specific survival (CSS) and OS than those with ASCC. However, after PSM, patients with AA were related to a favorable OS (p < 0.001), but a comparable CSS (p = 0.140) to those with ASCC. Age, sex, grade, surgery, and M stage were the independent prognostic factors of CSS for AA and were included in the establishment of a novel nomogram. Patients from the WCH database (n = 112) were used as an external validation cohort. The C-index of the nomogram was 0.78 and 0.735 in internal and external validation, respectively, which suggested the good discrimination power of the model. Furthermore, calibration curves and DCA suggested good agreement between the predicted and actual survival. Lastly, a risk classification system based on a nomogram revealed the reliability of the novel model. CONCLUSION: AA and ASCC had distinct clinical features. AA was associated with a better prognosis than ASCC after PSM. The model of nomogram showed an accurate predictive ability for prognostic factors of AA patients.